Articles | Volume 24, issue 7
https://doi.org/10.5194/nhess-24-2481-2024
https://doi.org/10.5194/nhess-24-2481-2024
Research article
 | 
19 Jul 2024
Research article |  | 19 Jul 2024

Revisiting regression methods for estimating long-term trends in sea surface temperature

Ming-Huei Chang, Yen-Chen Huang, Yu-Hsin Cheng, Chuen-Teyr Terng, Jinyi Chen, and Jyh Cherng Jan

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Cited articles

Boretti, A.: Analysis of segmented sea level time series, Appl. Sci., 10, 625, https://doi.org/10.3390/app10020625, 2020. 
Chang, M.-H.: Revisiting regression methods for estimating long-term trends in sea surface temperature, Zenodo [code and data set], https://doi.org/10.5281/zenodo.10360553, 2023. 
Chang, M.-H., Cheng, Y.-H., Yeh, Y.-Y., Hsu, J.-Y., Jan, S., Tseng, Y.-H., Sui, C.-H., Yang, Y. J., and Lin, P.-H.: Diurnal Sea Surface Temperature Warming along the Kuroshio off Taiwan under Easterly Wind Conditions, Geophys. Res. Lett., 50, e2022GL101412, https://doi.org/10.1029/2022GL101412, 2023. 
Chen, C., Wang, G., Xie, S., and Liu, W.: Why does global warming weaken the Gulf Stream but intensify the Kuroshio?, J. Climate, 32, 7437–7451, https://doi.org/10.1175/JCLI-D-18-0895.1, 2019. 
Cheon, W. G., Park, Y. G., Yeh, S.-W., and Kim, B.-M.: Atmospheric impact on the northwestern Pacific under a global warming scenario, Geophys. Res. Lett., 39, L16709, https://doi.org/10.1029/2012GL052364, 2012. 
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Short summary
Monitoring the long-term trends in sea surface warming is crucial for informed decision-making and adaptation. This study offers a comprehensive examination of prevalent trend extraction methods. We identify the least-squares regression as suitable for general tasks yet highlight the need to address seasonal signal-induced bias, i.e., the phase–distance imbalance. Our developed method, evaluated using simulated and real data, is unbiased and better than the conventional SST anomaly method. 
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